Utilization of Multi-Objective Genetic Algorithm (MOGA) to Optimize Maintenance Decision Support for Ordinary Arterial Highways

The maintenance and management of ordinary arterial highways has always faced many challenges, including limited resource allocation, complex maintenance needs, and constantly changing environmental conditions. The traditional maintenance methods for ordinary arterial highways often focus on optimizing a single objective, making it difficult to fully consider the mutual influence and balance between various factors. The article applied Multi-objective Genetic Algorithm (MOGA) to optimize decision support for maintenance of ordinary arterial highways. By considering multi-objectives such as maintenance costs, road surface smoothness, traffic congestion, security, and environmental impact, MOGA was used to search for the optimal maintenance plan. The empirical results indicated that MOGA could reduce the optimized road surface smoothness to a minimum of 40mm/m, providing an effective multi-objective optimization method for mainline highway maintenance decision-making, which helps to improve maintenance effectiveness and the sustainable development capacity of the transportation system.